activity
20242026
most citedGaussianFluent: Gaussian Simulation for Dynamic Scenes with Mixed Materials

1 citations · 1 across the 14 of their papers we have counts for

collaborators

15 papers

cs.CV2026

Seedance 2.0: Advancing Video Generation for World Complexity

Team Seedance, De Chen, Liyang Chen +168

Seedance 2.0 is a new native multi-modal audio-video generation model, officially released in China in early February 2026. Compared with its predecessors, Seedance 1.0 and 1.5 Pro…

cs.CV2026

SceneAssistant: A Visual Feedback Agent for Open-Vocabulary 3D Scene Generation

Jun Luo, Jiaxiang Tang, Ruijie Lu +1

Text-to-3D scene generation from natural language is highly desirable for digital content creation. However, existing methods are largely domain-restricted or reliant on predefined…

cs.CV2026★ 1 cited

GaussianFluent: Gaussian Simulation for Dynamic Scenes with Mixed Materials

Bei Huang, Yixin Chen, Ruijie Lu +4

3D Gaussian Splatting (3DGS) has emerged as a prominent 3D representation for high-fidelity and real-time rendering. Prior work has coupled physics simulation with Gaussians, but p…

cs.CV2025

G4Splat: Geometry-Guided Gaussian Splatting with Generative Prior

Junfeng Ni, Yixin Chen, Zhifei Yang +4

Despite recent advances in leveraging generative prior from pre-trained diffusion models for 3D scene reconstruction, existing methods still face two critical limitations. First, d…

cs.CV2025

VideoArtGS: Building Digital Twins of Articulated Objects from Monocular Video

Yu Liu, Baoxiong Jia, Ruijie Lu +5

Building digital twins of articulated objects from monocular video presents an essential challenge in computer vision, which requires simultaneous reconstruction of object geometry…

cs.CV2025

DreamArt: Generating Interactable Articulated Objects from a Single Image

Ruijie Lu, Yu Liu, Jiaxiang Tang +6

Generating articulated objects, such as laptops and microwaves, is a crucial yet challenging task with extensive applications in Embodied AI and AR/VR. Current image-to-3D methods…

cs.CV2025

Efficient Part-level 3D Object Generation via Dual Volume Packing

Jiaxiang Tang, Ruijie Lu, Zhaoshuo Li +7

Recent progress in 3D object generation has greatly improved both the quality and efficiency. However, most existing methods generate a single mesh with all parts fused together, w…

cs.CV2025

Decompositional Neural Scene Reconstruction with Generative Diffusion Prior

Junfeng Ni, Yu Liu, Ruijie Lu +4

Decompositional reconstruction of 3D scenes, with complete shapes and detailed texture of all objects within, is intriguing for downstream applications but remains challenging, par…

cs.CV2025

ArtGS: Building Interactable Replicas of Complex Articulated Objects via Gaussian Splatting

Yu Liu, Baoxiong Jia, Ruijie Lu +3

Building articulated objects is a key challenge in computer vision. Existing methods often fail to effectively integrate information across different object states, limiting the ac…

cs.CV2025

TACO: Taming Diffusion for in-the-wild Video Amodal Completion

Ruijie Lu, Yixin Chen, Yu Liu +5

Humans can infer complete shapes and appearances of objects from limited visual cues, relying on extensive prior knowledge of the physical world. However, completing partially obse…

cs.CV2024

Template-free Articulated Gaussian Splatting for Real-time Reposable Dynamic View Synthesis

Diwen Wan, Yuxiang Wang, Ruijie Lu +1

While novel view synthesis for dynamic scenes has made significant progress, capturing skeleton models of objects and re-posing them remains a challenging task. To tackle this prob…

cs.CV2024

MOVIS: Enhancing Multi-Object Novel View Synthesis for Indoor Scenes

Ruijie Lu, Yixin Chen, Junfeng Ni +5

Repurposing pre-trained diffusion models has been proven to be effective for NVS. However, these methods are mostly limited to a single object; directly applying such methods to co…

cs.CV2024

Superpoint Gaussian Splatting for Real-Time High-Fidelity Dynamic Scene Reconstruction

Diwen Wan, Ruijie Lu, Gang Zeng

Rendering novel view images in dynamic scenes is a crucial yet challenging task. Current methods mainly utilize NeRF-based methods to represent the static scene and an additional t…

cs.CV2024

RoomTex: Texturing Compositional Indoor Scenes via Iterative Inpainting

Qi Wang, Ruijie Lu, Xudong Xu +5

The advancement of diffusion models has pushed the boundary of text-to-3D object generation. While it is straightforward to composite objects into a scene with reasonable geometry,…

cs.CV2024

InTeX: Interactive Text-to-texture Synthesis via Unified Depth-aware Inpainting

Jiaxiang Tang, Ruijie Lu, Xiaokang Chen +3

Text-to-texture synthesis has become a new frontier in 3D content creation thanks to the recent advances in text-to-image models. Existing methods primarily adopt a combination of…